Your dissertation results chapter reports what your analysis found, presented clearly and without interpretation. It states the descriptive statistics, then the outcome of each inferential test tied back to a research question or hypothesis. The guiding rule is separation: the results chapter shows the findings, while the discussion chapter explains what they mean.
How to structure the chapter around your questions
The cleanest results chapters are organised by research question, not by software output. Open with a short paragraph that reminds the reader of your questions and signposts the order you will answer them. Present your sample characteristics and descriptive statistics first, then take each question in turn, reporting the relevant inferential test and its result before moving on. This question-by-question structure keeps a long chapter readable and shows your supervisor that every analysis you ran maps to a stated aim. The line between summarising your sample and generalising beyond it is the backbone of that order.
Presenting tables, figures, and the numbers
Tables and figures carry the detail so your prose can stay readable. Put full descriptive tables and large output where they belong, then use the text to highlight the one or two numbers that answer each question rather than repeating every cell. Each table and figure needs a number, a clear title, and a callout in the text so the reader knows when to look. Report each result with its test statistic, degrees of freedom, exact p-value, and an effect size, following APA reporting conventions so nothing is left ambiguous.
| Section | What it contains | What to leave out |
|---|---|---|
| Opening | Research questions and chapter map | New literature |
| Descriptives | Sample profile, means, frequencies | Interpretation of findings |
| Inferential results | Each test, by research question | Reasons the result occurred |
| Summary | Brief recap of key findings | Recommendations |
Results chapter vs discussion chapter: keeping them distinct
The single most useful boundary to hold is the line between the results chapter and the discussion chapter. The results chapter answers what you found: it states the numbers, the test outcomes, and which hypotheses were supported, with no claims about why. The discussion chapter answers what the findings mean: it interprets the results, links them to your literature, considers alternative explanations, and acknowledges limitations. A reliable test is to ask of every sentence whether it reports a fact or offers an opinion; facts belong in results, judgements belong in discussion.
Blurring the two is one of the most common reasons a chapter reads as unfocused. If you find yourself writing "this suggests" or "this is likely because" in your results, you have crossed into discussion territory and should move that sentence. Reporting an effect size alongside each test actually helps you hold the line, because it lets the results chapter convey how large a finding is without yet explaining why it occurred.
Reporting statistical significance without over-claiming
Within the results chapter, the way you handle statistical significance needs care. State the exact p-value rather than only "significant" or "not significant", and never describe a non-significant result as proof that no effect exists; absence of significance is not evidence of absence. Avoid loaded words like "prove" entirely, since a single study supports rather than proves a claim. Where you can, pair the p-value with a confidence interval around the estimate so the reader sees the precision behind the decision.
Consistency of language matters too. Decide on one threshold, report it in your methods, and apply it the same way throughout, so a reader is never left guessing what counted as significant. Understanding the meaning behind the number, set out in what a p-value actually tells you, keeps your phrasing accurate and stops small misreadings from accumulating into an overstated conclusion.
Common mistakes that cost marks
Two errors recur in draft results chapters. The first is interpreting findings too early, drifting into the discussion and explaining why a result appeared instead of simply reporting it. The second is presenting raw software output unedited, pasting full SPSS tables that bury the relevant figures; cleaning that output is part of the skill in making sense of your SPSS tables. A third quieter problem is using a test that does not fit the data, so confirm your choice against the decision logic for selecting a test before you write up anything.
Closing the chapter and handing off to the discussion
End with a brief summary that restates the key findings in plain language, with no fresh analysis and no interpretation. Note which hypotheses were supported and which were not, then signal that the meaning of these results is taken up in the next chapter. A tight close like this gives your committee a clean record of what you found and sets up the discussion to do the explaining, keeping the two chapters properly distinct.